The financial industry is undergoing a transformation—but not at the speed or in the way many expected. Instead of a sprint toward innovation, it’s looking more like a relay race. Traditional banks and fintech startups are passing the baton, each contributing different strengths along the way. Banks bring scale, trust, and regulatory muscle, while fintechs offer speed, creativity, and a willingness to disrupt.
At the center of this evolving landscape is AI in financial services, driving smarter operations, better user experiences, and new ways to solve old problems. The future of finance isn’t a solo run—it’s a coordinated effort.
Profitable Yet Sluggish: Banks at a Crossroads
Banks in the U.S. continue to post massive profits—over $268 billion recently. But loan growth is sluggish, hovering around just 1% per quarter. While their balance sheets are solid, their innovation pipelines often aren’t. Legacy systems, siloed data, and a culture of caution continue to slow progress. As a result, banks may have the resources, but they lack the urgency and flexibility to transform quickly.
Yet, banks are beginning to realize that profitability doesn’t guarantee survival. Emerging competitors—from embedded finance giants to nimble fintech challengers—are proving that customers want more than just stability. They want real-time solutions, intuitive interfaces, and value-added services built for the digital age.
AI in Financial Services Has Speed—But Struggle With Scale
Fintechs have no shortage of bold ideas. From personal financial management (PFM) tools to AI-enabled fraud detection and agentic AI models, startups are pushing boundaries. Venture funding recently rebounded above $10 billion, though that figure is skewed by a few mega-deals. Still, capital remains tight for most, and regulatory scrutiny is intensifying.
The challenge for fintechs isn’t ideation—it’s execution. While some break through with innovative use cases, many struggle to scale, monetize, or integrate into broader financial ecosystems. Success often hinges on partnerships with banks or infrastructure players, but that introduces new hurdles: integration complexity, cultural mismatch, and misaligned incentives.
The AI Hype Cycle: From Buzzwords to Real Value
Artificial intelligence is now an expected part of any fintech pitch. Whether it’s for automating compliance, predicting credit risk, or enhancing user engagement, AI has moved from a buzzword to a baseline. But the question remains: who’s actually using it well?
The current stage of AI in financial services is still exploratory. Many players are testing use cases, running pilots, and gauging impact. Some institutions are “all in” on AI, only to realize that full-scale implementation is much harder than anticipated. Others are quietly integrating AI into back-end processes like fraud detection or compliance management—and seeing real gains.
The key is to move beyond AI as a novelty and toward AI as an embedded capability. Soon, no one will talk about “using AI”—it will just be part of how financial products work, much like the internet or mobile banking today.
The Infrastructure Dilemma: Who Can Really Build for the Future?
Legacy infrastructure is one of the biggest blockers for incumbent banks. Mainframes, siloed databases, and outdated software make it incredibly difficult to implement modern AI capabilities or real-time payment rails. In contrast, fintechs and newer digital banks operate on cloud-native architectures that are far more adaptable.
This architectural gap is growing more significant as the financial industry moves toward autonomous operations, agentic AI, and blockchain-based transactions. The winners in this space will be those who can evolve their infrastructure fast enough to keep up with changing demands.
Companies like Stripe and PayPal are leading the charge here, blending financial services with modern tech stacks to enable faster, more flexible innovation.
Stablecoins and Real-Time Payments: Solving Real Problems?
Technologies like stablecoins and real-time payments have captured attention, but the market is still grappling with how to make them useful. While faster payments sound great on paper, customers care less about speed and more about solving everyday problems. Can a small business pay suppliers without cash flow delays? Can a gig worker access earnings instantly?
The challenge is to move past the “technology trigger” and toward practical applications that make a meaningful difference. Real-time payments, for instance, need to be paired with better cash flow management tools or integrated into operating systems for small and mid-sized businesses.
Compliance, Complexity, and the Deepfake Problem
One area where AI is already showing real value is in fraud prevention and compliance. Companies are using AI to identify transaction anomalies, monitor customer behavior, and even detect deepfakes. Yet, with increased power comes increased risk. A well-done spoof of a financial executive’s voice or image can be used for social engineering attacks.
This raises an important issue: user trust. Many consumers are uneasy about interacting with AI, especially if they’re unaware that they’re doing so. Some firms are now tracking “AI detection rates”—a measure of how often users can tell they’re speaking to a machine. The goal is not just to fool people, but to build AI tools so intuitive and helpful that people want to use them—consciously.
Bridging the Human Gap: Oversight in an AI-Driven World
As AI becomes more central to financial decision-making, one question looms: who’s watching the machines? Right now, many financial institutions lack internal talent with the skills to audit AI systems. Regulators are also struggling to keep up.
The solution may lie in third-party oversight. Specialized agencies or external watchdogs could monitor AI activity across institutions, ensuring fairness, transparency, and accountability. With more graduate programs producing AI and data science experts, the talent gap could close. But the governance model still needs to be built.
Platformification and the End of “Separate” Financial Services
Financial services are no longer something customers “go to.” They’re increasingly embedded into the platforms and workflows people already use. For small businesses, that means banking services baked into accounting software or payroll tools. For consumers, it might mean getting a loan offer while shopping online or accessing budgeting tools through a ride-share app.
This “platformification” trend changes the game for banks and fintechs alike. The fight for customer attention won’t happen on bank websites—it will play out in ecosystems like e-commerce platforms, business software, and social media. Success will depend on partnerships, APIs, and the ability to integrate seamlessly into people’s digital lives.
The Future Belongs to the Curious, Critical, and Bold
What this all adds up to is simple: the financial industry is in transition. The winners won’t be the ones who cling to legacy systems or chase every shiny new trend. Instead, they’ll be the institutions and innovators who balance experimentation with execution—who listen to real customer problems and build solutions that solve them.
Whether your foundation is a century-old bank charter or a Series A startup pitch, the finish line is the same: smarter, safer, and more human-centric financial experiences through AI in financial services.
